Many physiological activities have electrical signals associated therewith. For example, the operation of the heart is regulated by electrical signals produced by the heart's sinoatrial (SA) node. Normally, the SA node produces an electrical impulse roughly 60 times a minute.
Each impulse generated by the SA node initially spreads across the atria of the heart. After reaching the atrioventricular (AV) node of the heart, the impulse then travels downward to the ventricles. The electrical impulse depolarizes the muscle fibers as it spreads, with atrial and ventricular contractions occurring after the impulses pass. After contracting, the muscle cells are unable to react again for a short interval of time known as the refractory period. Eventually, the muscle fibers repolarize and return to their resting state.
As will be appreciated, the electrical activity initiated by the SA node is, thus, representative of the operation of a patient's heart. To allow the heart's operation to be analyzed, a variety of techniques have been developed for collecting and interpreting data concerning the electrical activity of the heart. Perhaps the most basic of these approaches is the three-lead electrocardiogram (ECG).
A three-lead ECG system typically employs a monitor and four "limb" electrodes, attached to the patient, to collectively monitor three voltages or "leads." Specifically, a left arm electrode (L) is placed on the patient's left arm. Similarly, a right arm electrode (R) is placed on the patient's right arm. A left leg electrode (F) is attached to the patient's left leg and a right leg or "ground" electrode (G) is attached to the patient's right leg.
As an electrical impulse spreads across the heart, the monitor repetitively measures the voltages at electrodes L, R, and F, relative to the ground electrode G. These voltages are designated vL, vR, and vF, respectively.
The first of the leads (I) evaluated by the monitor is equal to the difference between the voltages at electrodes L and R (I=vL-vR). Similarly, the second lead (II) monitored with the electrodes is equal to the difference between the voltages at electrodes F and R (II=vF-vR). Finally, the third lead (III) evaluated by the monitor is equal to the difference between the voltages at electrodes F and L (III=vF-vL).
The waveforms produced by plotting each of the leads over an interval of time corresponding to one cardiac cycle are conventionally divided into a number of segments. The portion of each waveform representing atrial depolarization is referred to as the "P" segment or wave. Depolarization of the ventricular muscle fibers is then represented by "Q," "R," and "S" segments of the waveform. Finally, the portion of the waveform representing repolarization of the ventricular muscle fibers is known as the "T" segment or wave.
To simplify the analysis of the three leads I, II, and III of data, the heart is generally treated as a dipolar source of electrical activity, positioned at the intersection of transverse, superior, and inferior axes of the patient's body. Each of the three leads is regarded as being equally sensitive to all sections of the heart. Lead I is, however, interpreted as representing electrical activity on the transverse axis, while leads II and III are interpreted as representing activity on the superior and inferior axes.
As will be appreciated, the leads are influenced by a variety of factors. For example, the size of the patient's heart, as well as its location and orientation relative to the patient's trunk, will affect the magnitudes of the leads. The presence of heart disease will also typically impact the waveforms. Further, the size, fat content, and air content of the patient's trunk, as well as the existence of any physical deformities or diseases, may influence the waveforms. Finally, the relative positioning of the electrodes on the patient may alter the waveforms sensed.
To properly interpret the three leads I, II, and III of data, a physician must be trained to recognize and identify the influence of these various factors. The physician must also understand the dipolar cardiac model and the resultant relationship between the three leads and the cardiac activity of interest.
In that regard, a physician's analysis of three-lead ECG data typically begins with the selection of the particular lead or leads to be reviewed. In that regard, because lead I reflects cardiac activity on the transverse body axis, the physician would most likely review lead I to detect lateral infarction or coronary vessel involvement. Similarly, because leads II and III reflect cardiac activity on the superior-inferior axes of the patient's body, they are reviewed to detect, for example, inferior disease.
Having selected a lead for analysis, the physician typically makes an initial assessment based upon the overall appearance of the waveform. The physician must also recognize the significance of particular features of the waveform. In that regard, a number of waveform features have been identified for use in diagnosing various heart conditions.
The area of the "QRST" segment of the waveform has been recognized as indicating disparity of recovery properties. As will be appreciated, the waveform's area can be computed by integrating the waveform over the interval of time during which the ventricular muscle fibers are depolarized and repolarized. A change in QRST area may indicate the presence of disease.
Another waveform feature used to diagnose the heart's condition is an analysis of the "ST" segment of the waveform. In that regard, the displacement of the ST segment is generally indicative of acute injury. For example, an elevated ST segment associated with Q waves indicates an acute or recent infarct. The analysis of the ST segment is usually based upon data collected from more than the three leads describes above.
A related form of analysis is referred to as "late-potential" analysis. Late-potential analysis involves the expansion of the time-scale of the QRS segment of the waveform and a detailed review of the expanded segment for features not apparent in a conventional display of the waveform. More particularly, the expanded segment is reviewed for low level activity that persists into the ST segment.
While the three-lead system described above is generally useful in evaluating the condition of the patient's heart, it does have certain limitations. For example, because the three-lead analysis is based upon a dipolar view of the heart, the leads have little selective sensitivity to the operation of particular regions of the heart. Depending upon the nature of the cardiac event to be detected, this lack of sensitivity may prevent the three-lead data from being diagnostically useful.
One effort to increase the regional sensitivity of ECGs led to the development of "12-lead" ECGs. A 12-lead ECG system includes the limb electrodes of a conventional three-lead ECG system. In addition, a 12-lead system includes six "precordial" electrodes, positioned on the patient's chest. The six precordial electrodes were originally added to allow the electrical activity of individual regions of the heart to be more directly sensed. In practice, however, the dipolar model of the heart has been retained and the 12 leads interpreted to evaluate electrical activity along the three axes.
Although the 12-lead ECG configuration has been described as allowing a limited form of "mapping" to be performed, for the purposes of the ensuing discussion it will be more precisely referred to as a technique for introducing selective sensitivity into the leads of an ECG system. In contrast, as will be described in greater detail below, mapping is more appropriately used to describe approaches involving the evaluation or presentation of spatial distributions of data over the patient's chest.
Reviewing the construction and operation of a 12-lead ECG system in greater detail, as noted above, six precordial electrodes are added to the four limb electrodes of a three-lead ECG system. In that regard, a first precordial electrode (p1) is attached to the front of the patient's chest, to the right of the sternum in the fourth rib interspace. A second precordial electrode (p2) is also attached to the front of the patient's chest, left of the fourth rib interspace. A fourth precordial electrode (p4) is positioned at the left midclavicular line in the fifth rib interspace. The third precordial electrode (p3) is positioned midway between electrodes p2 and p4. Finally, the fifth precordial electrode (p5) is positioned at the midaxillary line in the fifth rib interspace and the sixth precordial electrode (p6) is positioned midway between electrodes p4 and p5.
The 12 leads or waveforms evaluated with the four limb electrodes and six precordial electrodes are as follows. In addition to the three leads I, II, and III already described, three leads aVR, aVL, and aVF are formed from the voltages sensed at the limb electrodes. In that regard, lead aVR=vR-(vL+vF)/2; lead aVL=vL-(vR+vF)/2; and lead aVF=vF-(vL+vR)/2.
The six precordial electrodes p1, p2, p3, p4, p5, and p6 are used to sense voltages v1, v2, v3, v4, v5, and v6, respectively, referenced to the ground electrode G. The remaining six leads are designated V1, V2, V3, V4, V5, and V6. In that regard, lead V1=v1-(vR+vL+vF)/3; lead V2=v2-(vR+vL+vF)/3; lead V3=v3-(vR+vL+vF)/3; lead V4=v4-(vR+vL+vF)/3; lead V5=v5-(vR+vL+vF)/3; and lead V6=v6-(vR+vL+vF)/3.
As will be appreciated, the 12 waveforms produced by such a system each have the various PQRST segments described above. In analyzing the 12-lead data, the physician may consider the overall appearance of the waveforms, as well as the various waveform features discussed above in connection with the three-lead system. In addition, because the 12-lead ECG contains considerably more information than the conventional three-lead ECG, the physician may choose to review only a few of the numerous leads, with the particular leads selected depending upon the cardiac features of interest.
In that regard, the dipolar model of the heart is almost universally relied upon in the analysis of 12-lead ECGs. Leads I, aVL, aVR, V5, and V6 reflect cardiac activity on the transverse body axis and are monitored to evaluate lateral disease. Leads II, III, and vF are indicative of electrical activity on the superior-inferior axis and are reviewed to evaluate inferior disease. Finally, leads V1, V2, V3, and V4 represent activity on the anteroposterior axis and are monitored to determine anterior and posterior disease.
One alternative use of the conventional 12-lead ECG system described above is the performance of a stress test. The system is virtually the same with the exception that electrodes L and R are moved from the patient's arms to the trunk. As a result, leads I, II, III, aVR, aVL, and aVF are attenuated. Cardiac stress is introduced by subjecting the patient to a regimen of vigorous exercise and the resultant leads are analyzed in conventional fashion.
As noted previously, although the 12-lead ECG originally represented an effort to adopt a regionally differentiated model of cardiac activity in place of the dipolar model, both the three-lead and 12-lead ECG are conventionally analyzed as representing the activity of a dipolar cardiac generator. Serious efforts to provide selective sensitivity to the operation of particular regions of the heart were initiated by the introduction of body surface mapping (BSM) systems. Such systems evaluate or present spatial distributions of data over the patient's chest.
Conventional body surface mapping systems employ a relatively large number of electrodes in comparison to the three-lead and 12-lead ECG systems described above. For example, much of the work done in the area of body surface mapping has been with systems employing 192 electrodes. As will be appreciated, the use of such a large number of electrodes allows the spatial distribution of voltage across the patient's chest to be relatively closely evaluated.
Unlike the ECGs discussed above, in which each lead is displayed as a time-dependent waveform, the voltages sensed at the BSM electrodes are often plotted as part of a map of the patient's chest. More particularly, the two-dimensional layout of the electrodes relative to the patient is first plotted. Then, for each point in the cardiac cycle at which measurements are made, the electrode sites having the same voltages are connected by contour lines, commonly referred to as "isopotential" lines. As a result, a series of isopotential maps are generated for for each cardiac cycle.
Although the generation of isopotential maps is relatively easy to accomplish, their interpretation can be difficult. In that regard, some relationship between the contours of the isopotential map and the particular cardiac features of interest must be established. Although a physician can make an initial evaluation based upon visual comparisons with referential maps generated for populations of known physiology, the volume of data contained in the series of maps generated over one cardiac cycle can be overwhelming. Further, because mapping is not presently widely performed, the physician's experience and familiarity with referential maps may be somewhat limited.
A variety of techniques have been developed to reduce the complexity of map analysis. For example, one way of reducing the volume of data to be dealt with involves integration of the voltages sensed at each of the electrodes over an interval of time. In that regard, if the voltage at a given electrode is plotted as a function of time, the resultant waveform generally includes the P, Q, R, S, and T segments described above. By integrating that voltage over, for example, the QRS or ST interval, a single value indicative of the sensed voltage at the electrode is produced.
A single isointegral map, representative of cardiac activity over an entire cycle, can then be generated as follows. As with the isopotential map, the two-dimensional arrangement of the electrodes relative to the patient's chest is first plotted. Next, the integrals of the waveforms at the various electrode sites are evaluated and those electrode sites having the same integral values associated therewith are connected by lines, commonly referred to as "isointegral" contours. As a result, a single isointegral map is produced representing cardiac activity over one cycle.
Even with the data reduced to a single map per cardiac cycle, interpretation can be somewhat difficult. Each map includes a multitude of potentially significant contours to be evaluated by the physician. The experience required to meaningfully interpret these contours based solely upon a visual review is considerably more extensive than that required to evaluate 12-lead ECGs. Such evaluation is further hampered by the relatively limited information available correlating map contours with cardiac activity.
To enhance the value of such maps, increasing efforts are being made to identify significant map features and to develop systems that automatically extract such features from map data. With the appropriate features extracted, a physician can then more quickly and easily interpret the data.
In that regard, one approach to feature extraction that is of particular interest is described in an article by Lux et al., entitled "Redundancy Reduction for Improved Display and Analysis of Body Surface Potential Maps, I. Spatial Compression," appearing in Volume 49 of Circulation Research at pages 186-196. Lux et al. disclose an approach in which a Karhunen-Loeve transform is used to compress the data to produce a basis function vector that allows the data to be reconstructed with minimum representational error. A stepwise discriminant analysis is then applied to the vector coefficients to classify the patient as diseased or normal. While the Lux et al. approach is a useful tool in the evaluation of BSM data, as will be described in greater detail below, the disclosed technique fails to consider the potential influence of noncardiac patient variables on the analysis and does not adequately address the extraction of particular features of interest from the data.
In addition to reducing the complexity of BSM data analysis, attempts have been made to reduce the complexity of the data collection process. As will be appreciated, with 192 electrodes required to successfully generate a surface distribution of electrical activity, the time required to prepare a patient for data collection is significant. The electrode set required is further unwieldy, expensive, and may contribute to patient apprehension. Each of these factors tends to limit the utility of BSM data analysis.
One work that is of particular interest in the area of "limited-lead" mapping is the article by Lux et al., entitled "Clinically Practical Lead Systems for Improved Electrocardiography: Comparison with Precordial Grids and Conventional Lead Systems," appearing in Volume 59 of Circulation at pages 356-363. In this article, Lux et al. investigate the utility of several different lead sets in replicating the data collected with "conventional" 192 electrode BSM systems. More particularly, sets of 32, 30, and 9 leads are evaluated. Data collected from the limited leads is then transformed to represent data collected from a conventional lead set. Based upon the evaluation of this transformed data, Lux et al. conclude that 20-35 electrodes are required for BSM analyses.
More particularly, Lux et al. emphasize numerous shortcomings of the nine lead data transformation. For example, Lux et al. note that the pattern error and root-mean-square (rms) error for the nine-lead set is larger than the errors occurring when 32-lead arrays are used. Lux et al. conclude that the nine-lead array misses electrocardiographic information and that 20-35 electrodes are required for mapping.
Efforts have also been devoted to the use of BSM data to identify particular cardiac anomalies of interest. For example, the subject of coronary artery narrowing is addressed in an article by Farr et al., entitled "Localization of Significant Coronary Arterial Narrowings Using Body Surface Potential Mapping During Exercise Stress Testing," appearing in Volume 59 of the American Journal of Cardiology at pages 528-530, and an article by Sridharan et al., entitled "Use of Body Surface Maps to Identify Vessel Site of Coronary Occlusion," appearing in Volume 22S of the Journal of Electrocardiology at pages 72-81. As will be described in greater detail below, however, these approaches are limited by the form of the data analyzed, the feature extraction techniques used, and their ability to quantify, as well as localize, arterial narrowings.
Another specific anomaly of interest is the heart's "inducibility", or susceptibility to externally induced arrhythmia. The subject of inducibility is addressed to some extent, for example, in an article by Vincent et al. entitled "Use of QRST Area Distribution to Predict Vulnerability to Cardiac Death Following Myocardial Infarction", appearing in Volume 68 of Circulation at page 352, an article by Kubota et al. entitled "Relation of Cardiac Surface QRST Distribution to Ventricular Fibrillation Thresholds in Dogs", appearing in Volume 78 of Circulation at pages 171-177, and an article by Han et al., entitled "Nonuniform Recovery of Excitability in Ventricular Muscle", appearing in Volume 14 of Circulation at pages 44-60. Again, however, the disclosed approaches are somewhat limited in nature and applicability.
As will be appreciated from the preceding discussion, it would be desirable to provide a system that would allow a spatial distribution representative of, for example, the electrical activity of a heart to be analyzed without requiring the use of complex electrode configurations for data collection. The system should, however, take advantage of the added information content present in the spatial distribution. In addition, the system should format the spatially distributed data in a manner suitable for the particular feature to be extracted. The system should further be able to extract the features in a manner that distinguishes noncardiac influences on the data and that offers increased analytical capabilities with respect to particular features of interest.